Prefrontal Cortex, Thalamus, and Cerebellar Volumes in ...

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BRAIN VOLUMES IN YOUTHS 1593 cooperation, and image quality. We required that the midsagittal slice show full visualization of the cerebral aqueduct and the anterior and posterior commissures, in which a line was estimated requiring the anterior-commissure-posterior-commissure line to be within three degrees of 180. If these criteria were not met, the subject was realigned until these criteria were met. A three-dimensional spoiled gradient recalled acquisition in the steady-state pulse sequence was used to obtain 124 contiguous images with slice thickness of 1.5 mm in the coronal plane for region of interest measures (TE � 5 msec, TR � 25 msec, flip angle � 40 degrees, acquisition matrix � 256 � 192, number of excitations � 1, field of vision � 24 cm). Coronal sections were obtained perpendicular to the anteriorcommissure-posterior-commissure line to provide a more reproducible guide for image orientation. Axial proton density and T 2-weighted images were obtained to enable exclusion of structural abnormalities on MRI. A neuroradiologist reviewed all scans and ruled out clinically significant abnormalities. All subjects tolerated the procedure well. No sedation was used. The imaging data from the coronal sections were transferred from the MRI unit to a computer workstation (PowerMacintosh, Apple Computer) and analyzed with the use of IMAGE software (version 1.61) developed at the NIH (Rasband, 1996) that provides valid and reliable volume measurements of specific structures using a manually operated (hand tracing) approach. Trained and reliable raters who were blinded to subject information made all measurements. These methods were previously described by our group (De Bellis et al., 1999; De Bellis et al., 2002; De Bellis et al., 2001) and are briefly presented here. Intracranial volumes were calculated by first manually tracing the intracranial volume of each coronal slice after exclusion of skull and dura, then summing these areas of successive coronal slices, including GM and WM and cerebral spinal fluid (CSF) volumes, and multiplying by slice thickness. These measures included frontal, parietal, temporal, occipital cortex, subcortical structures, cerebellum, and brainstem. Cerebral volumes were measured after manual exclusion of CSF volumes, cerebellum, and brainstem in the same manner and included cortical and subcortical structures. Prefrontal cortex volumes were calculated by summing up areas of successive coronal slices, including gray and white matter and CSF volumes and multiplying by slice thickness. The anterior boundary of the prefrontal cortex was defined as the most anterior coronal section containing gray matter. The coronal slice showing the genu of the corpus callosum was used to mark the posterior limit of the prefrontal cortex (Rosenberg et al., 1997). Prefrontal white and gray matter volumes were calculated by using a semiautomated segmentation algorithm. This computerized segmentation technique uses mathematically derived cutoffs for gray matter–white matter–CSF partitions with histograms of signal intensities. This computerized segmentation technique is both labor intensive and manually operated. It uses an interactive method in which mathematically derived cutoffs for gray matter–white matter–CSF partitions from histograms of signal intensities are used to individually select gray matter, white matter, and CSF areas from each coronal slice. Gray matter, white matter, and CSF areas are thus separately calculated and multiplied by slice thickness for the individual subject’s gray matter, white matter, and CSF volumes. In this way, we can minimize the inherent limitations on qualifying white matter signal hypointensities as gray matter on T 1weighted MRI scans by visual inspection of slices (i.e., so that hypointensity artifacts in corpus callosum or cerebral white matter are not calculated as gray matter). This approach has been validated by using both a stereology technique for brain morphometric measurements and a phantom with known absolute volumes (Keshavan et al., 1995) and has been used in several published neuroimaging studies (De Bellis et al., 1999; De Bellis et al., 2001; Rosenberg et al., 1997). See Fig. 1. The boundaries of the thalamus were previously described (Gilbert et al., 2000). The boundaries of the thalamus were defined as follows: The mammillary bodies and the interventricular foramen defined the anterior boundary; the internal capsule defined the lateral boundary; the third ventricle defined the medial boundary; the hypothalamus defined the inferior boundary; the lateral ventricle defined the superior boundary; and Fig. 1. Manual tracings of PFC. PFC volumes were calculated by summing up areas of successive coronal slices and multiplying by slice thickness. The anterior boundary of the prefrontal cortex was defined as the most anterior coronal section containing gray matter. The coronal slice showing the genu of the corpus callosum was used to mark the posterior limit of the prefrontal cortex. Prefrontal white and gray matter volumes were calculated by using a semiautomated segmentation algorithm (not shown). the crus fornix defined the posterior boundary of the thalamus. Every coronal slice that included the thalamus was manually traced, and total volume was computed by summing up successive areas and multiplying by slice thickness. The volumes of the cerebellum, vermis, and brainstem were calculated by summing up areas of successive coronal slices after tracing the region of interest and excluding CSF as previously described (Hardan et al., 2001). Briefly, measurements began as the cerebellum appeared laterally to the pons. The tentorium cerebelli acted as the superior limit and the base of the cerebellum itself as the inferior limit. The cisterna magna and transverse sinus were excluded. The last slice included was the one at which the cerebellum was no longer distinguishable from the transverse sinus or disappeared. The measurement of the vermis began at the slice where the anterior and/or inferior posterior lobes appeared. The gray matter of the vermis structures, determined by mathematically derived cutoffs for gray matter–white matter–CSF partitions from histograms of signal intensities as previously described (De Bellis et al., 2001), were traced separately until the slice where the fourth ventricle was no longer visible. The cerebellar medullary body and the deep cerebellar nuclei were excluded. Measurements were made around the vermis until it was no longer visible. The first slice of the brainstem was measured where the pons first appeared within the suprasellar cistern. The cerebellar peduncles, including the brachium pontis (middle), were included in the brainstem. In the anterior plane, the superior limit of the pons was a straight line connecting the ambient cisterns from left to right. Posterior measurements included the cerebral aqueduct and the superior colliculus. No separate volumetric measurements were made for the midbrain, pons, and medulla oblongata. See Fig. 2. Intraclass correlation of interrater and intrarater reliability for independent designation of regions on segmented images obtained from 20 subjects were 0.99 and 0.99 for intracranial volume, cerebral volume, cerebral CSF, prefrontal lobe volume, prefrontal lobe gray matter, prefrontal lobe white matter, prefrontal CSF; 0.96 and 0.98 respectively, for right, left, and total thalamus volumes; 0.91 and 0.95 respectively, for right, left, and total cerebellum; 0.89 and 0.94 respectively, for pons/brainstem; and 0.91 and 0.92 respectively, for cerebellar vermis. Statistical Methods Demographic variables were compared by means of Student’s t test and Pearson 2 as appropriate. Histograms were obtained to assess normality of the data and to observe any outlying observations. There were no significant outliers, and we did not exclude any cases in our data analyses. Formal hypothesis testing was carried out by t tests in two stages, first with the raw data, then again adjusting for total cerebral volume, to determine differences between AUD subjects and control subjects. In testing for covariate effects such as sex and interactions (sex-by-group), multivariate regression analysis was used. Brain structural means, which differed significantly between the groups (e.g., PFC volumes), were adjusted for cerebral volume to correct for individual differences in brain size with regard to gender and then correlated with clinical data using Spearman correlation coefficients. All significance testing involving the main hypoth-
1594 DE BELLIS ET AL. Fig. 2. Manual tracings of cerebellum, vermis, and brainstem. The volumes of the cerebellum, vermis, and brainstem were calculated by summing up areas of successive coronal slices after tracing the region of interest. Measurements began as the cerebellum appeared laterally to the pons (not shown). The last slice included was the one at which the cerebellum was no longer distinguishable from the transverse sinus or disappeared (not shown). The measurement of the vermis began at the slice where the anterior and/or inferior posterior lobes appeared (A). This slice included the brainstem. The gray matter of the vermis structures, determined by mathematically derived cutoffs for gray matter–white matter–CSF partitions from histograms of signal intensities, were traced separately (B, C, D, E). Measurements were made around the vermis until it was no longer visible within the cerebellar hemispheres (F). The first slice of the brainstem was measured where the pons first appeared within the suprasellar cistern (not shown). The cerebellar peduncles, including the brachium pontis (middle), were included in the brainstem (A). Posterior measurements included the cerebral aqueduct and the superior colliculus. No separate volumetric measurements were made for the midbrain, pons, and medulla oblongata. esis was two-tailed with � 0.05. All data are presented as mean � SD unless otherwise specified. RESULTS Subjects with an adolescent-onset AUD had smaller PFC (p � 0.02) and PFC white matter (p � 0.007) volumes and greater amounts of PFC CSF (p � 0.01) compared with healthy comparison subjects. Smaller PFC (p � 0.02), PFC white matter (p � 0.004), and larger PFC CSF (p � 0.001) volumes persisted when controlling for cerebral volume. See Table 3. These results also persisted when controlling for cerebral volume and age, sex, and sex-by-group interactions for smaller PFC (F 1,36 � 5.8, p � 0.02) and PFC white matter (F 1,36 � 9.0, p � 0.005), and larger PFC CSF (F 1,36 � 12.0, p � 0.001) volumes. No effects of age, sex, or sex-by-group were seen in these analyses. Given that both major depression (Steingard et al., 2002) and ADHD (Castellanos et al., 1996; Mostofsky et al., 2002; Sowell et al. 2003a) in adolescents has been associated with smaller frontal volumes, multivariate regression analysis was used to further examine the results using comorbidity (number of comorbid disorders), sex, sex-by-group, and using PFC outcome variables least squares adjusted for cerebral volume. Although these analyses have decreased power, the results did confirm larger PFC CSF (F 1,37 � 5.27, p � 0.03) in subjects with an adolescent-onset AUD and suggested that subjects with an adolescent-onset AUD had smaller PFC (F 1,37 � 2.73, p � 0.1) and smaller PFC white matter volumes (F 1,37 � 2.4, p � 0.1), compared with healthy comparison subjects. Furthermore, multivariate regression analysis examining PFC variables using comorbidity (presence of major depression, presence of ADHD), presence of a cannabis use disorder, and controlling for sex and cerebral volume did confirm larger PFC CSF (F 1,34 � 9.0, p � 0.005) in subjects with an adolescent-onset AUD and suggested that subjects with an adolescent-onset AUD had smaller PFC suggested smaller PFC (F 1,34 � 2.4, p � 0.1), compared with healthy comparison subjects. The estimates for these comorbidities in these above regression models were not significant. To further explore this issue of comorbidity, we ran the following analyses. There were no significant differences when PFC volumes (adjusted for cerebral volumes) in AUD subjects with major depression (mean, 162.2 � 14.2 cm 3 ) and without major depression (mean, 155.7 � 15.2 cm 3 )(t 1,12 � -0.77, p � 0.45) were compared within AUD groups or when AUD subjects with ADHD (mean, 159.9 � 9.2 cm 3 ) and without ADHD (mean, 161.0 � 18.7 cm 3 )(t 1,12 � 0.13, p � 0.89) were compared within AUD groups. There were no significant differences when PFC volumes adjusted for cerebral volumes in AUD subjects with a cannabis use disorder (mean, 160.7 � 16.1 cm 3 ) and without a cannabis use disorder (mean, 159.3 � 3.5 cm 3 ) were compared within AUD groups (t 1,12 � -0.14, p � 0.89). Furthermore, there were no
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